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Last week, Microsoft announced a $60 million, multiyear commitment to the Department of Energy\u2019s (DOE\u2019s) Genesis Mission, the national initiative to embed artificial intelligence (AI) across the country\u2019s 17 national laboratories. The company\u2019s stated goal, echoing DOE\u2019s own framing, is to help \u201cdouble the productivity and impact of American research and innovation within a decade.\u201d Two nuclear energy projects anchor the announcement: a research reactor at Purdue University that Idaho National Laboratory (INL) helped adjust remotely and autonomously using distributed cloud computing, and an AI tool built to speed up the document-heavy work of nuclear licensing.<\/p>\n
Bryan Lopez, Microsoft\u2019s senior director for Federal Strategic Science Missions, offered POWER insight on what each project actually involves and where the company sees them heading next. Together with background materials on the underlying lab work, the picture that emerges is one of real, specific progress on a research reactor and a documentation tool\u2014building blocks toward a longer-term goal of AI-assisted nuclear deployment.<\/p>\n
A $60 Million Deal, Structured in Two Parts<\/p>\n
Microsoft\u2019s investment, detailed in a blog post<\/a> by Chris Barry, president of the company\u2019s U.S. Public Sector Industries business, breaks into two pieces: $40 million in Azure compute and AI credits distributed over three years, meant to give researchers \u201croom to train, simulate and iterate at a scale that matches their ambition,\u201d and $20 million in solution engineering enablement services\u2014dedicated engineering, architecture, deployment, and adoption support intended to convert that cloud capacity into results labs can actually use.<\/p>\n Alongside the money, Microsoft is standing up a new coordination hub called SPARK\u2014Scientific Partnership Advancing Research and Knowledge\u2014which the company describes as the \u201csingle front door\u201d for Genesis Mission collaboration with Microsoft. Lopez was specific about what that means in practice. \u201cSPARK isn\u2019t a computing platform or a pool of compute,\u201d he explained. \u201cWhen we call it the \u2018single front door,\u2019 we mean coordination and support, not infrastructure: SPARK helps projects onboard, manages how Azure credits and capabilities are allocated, and provides a dedicated bench of Azure- and AI-skilled specialists to help teams execute.\u201d He described it as \u201cthe people-and-project layer that helps researchers get the most out of the platform\u201d\u2014complementary to what labs already have, rather than a replacement for it.<\/p>\n SPARK is built around five stated commitments: a dedicated Genesis Mission program management office to handle intake and reporting; an \u201cAI for Science Center of Excellence\u201d to move projects from concept to deployment; optimization of how Azure credits get allocated across projects; management of technical services to help labs adopt AI capabilities; and joint research and development on Genesis Mission\u2013aligned challenge problems co-developed with DOE scientific leadership.<\/p>\n One practical question raised by the three-year credit structure is what happens to lab workloads once the initial funding is drawn down. Lopez said the arrangement is designed for continuity. \u201cAs the three-year investment is drawn down by project teams, workloads don\u2019t simply switch off when allocations are exhausted,\u201d he said. \u201cProjects that need to continue can pursue additional investment, and Microsoft\u2019s dedicated program office works directly with each project to identify the right next steps for ongoing funding and payment\u2014whether that\u2019s further co-investment, Department of Energy funding, or the cost-management path being built into the platform from the outset.\u201d The goal, he said, is \u201ca positive, uninterrupted experience for the research teams, with a clear plan for what comes after the initial credits.\u201d<\/p>\n Testing Autonomous Reactor Operations, One Step at a Time<\/p>\n The nuclear example Microsoft\u2019s announcement leads with is a project run by INL involving autonomous remote operation of a research reactor. Asked what the demonstration showed and how it fits into the longer path toward licensed deployment, Lopez described it as meaningful, bounded progress: \u201cThis was a successful demonstration of autonomous reactor power adjustments on a research reactor using distributed computing and cloud infrastructure, with safety systems always retaining control,\u201d he said. \u201cIt is an important step forward for nuclear innovation.\u201d<\/p>\n INL provided more detail in a July 13 news release<\/a>. It said researchers from the lab, the University of Illinois Urbana-Champaign\u2019s Grainger College of Engineering, and Purdue University used a geographically distributed control system to remotely and automatically adjust the power of PUR1, a low-power research reactor at Purdue, with the reactor\u2019s own safety systems retaining full control throughout. The team first built an automatic digital control loop, then made it more autonomous with a reinforcement learning model. The demonstration linked three sites in real time: high-performance computing systems in Idaho, the PUR1 reactor in Indiana, and a Microsoft Azure cloud environment in Virginia. From Idaho Falls, the team fine-tuned reactor power and carried out live autonomous adjustments without any manual control-rod manipulation on site.<\/p>\n \u201cResearching autonomous operations is essential to the future of nuclear energy; it\u2019s a key component of making future nuclear power plants safer, more efficient and more reliable,\u201d said Chris Ritter, INL\u2019s Scientific Computing and AI division director. \u201cThe idea is that if you can model a reactor with enough fidelity, you can eventually let AI safely assist in operating it. The safety case is what makes this real: the system analyzes, predicts, and adjusts, but the reactor\u2019s own safety controls always have the final say in this experiment.\u201d INL said the approach \u201caligns with Nuclear Regulatory Commission (NRC) requirements by operating alongside, not in place of, the reactor\u2019s safety control systems\u201d\u2014a design principle consistent with how Lopez described Microsoft\u2019s role in the work.<\/p>\n Speeding Up Licensing Paperwork, With Engineers Still in the Loop<\/p>\n The other nuclear-focused piece of Microsoft\u2019s Genesis Mission work involves applying AI to nuclear licensing and permitting. Asked which parts of that process Microsoft is targeting, Lopez said, \u201cOur current focus is on the most document-intensive portions of the licensing and permitting process, where engineers and subject matter experts spend significant time drafting, cross-referencing, validating, and updating large volumes of technical and regulatory documentation.\u201d He noted, \u201cAI is being applied to document drafting, gap analysis, consistency checking, and the unification of project information needed to support licensing and permitting applications,\u201d with the aim of making those workflows \u201cmore repeatable, traceable, auditable, and efficient while maintaining engineering accountability and regulatory rigor.\u201d The intent, as he put it, is for AI to handle portions of the documentation workload so that \u201cengineers and regulators can focus their attention on technical and safety judgments rather than manually reconciling thousands of pages of text.\u201d<\/p>\n That description aligns with how INL and Microsoft characterized their original collaboration on this front. In an announcement from July last year<\/a>, INL said it would use \u201ca Microsoft-developed solution built with Azure AI services to generate engineering and safety analysis reports, which are standard reports submitted as a part of applications for construction permits and operating licenses for nuclear power plants.\u201d At the time, Jess Gehin, INL\u2019s associate laboratory director for Nuclear Science and Technology, called the work \u201ca big deal for the nuclear licensing process,\u201d adding that \u201cintroducing AI technologies will enhance efficiency and accelerate the deployment of advanced nuclear technologies.\u201d<\/p>\n The tool\u2019s role was specifically scoped: \u201c[It] does not perform analyses on the documents but rather automates the process of constructing licensing documents for subsequent human verification,\u201d INL explained. Ritter, commenting on the collaboration, framed it as the start of an important national effort: \u201cAI holds significant potential to accelerate the process to design, license, and deploy new nuclear energy for the nation\u2019s increasing energy needs. INL looks forward to early research to evaluate the applicability of generative AI in the nuclear licensing space.\u201d<\/p>\n Meanwhile, the NRC has its own views on AI. Its public materials show an agency building out AI governance and use cases in parallel: an internally developed tool called SimplifAI, used for text retrieval and generation, is listed in the agency\u2019s use-case inventory as \u201cdeployed\u201d to support licensing, oversight, and other regulatory activities, alongside Microsoft 365 Copilot for administrative tasks; a unified platform for accessing multiple AI models and testing of additional large language models remain in \u201cpre-deployment\u201d status. Separately, the NRC completed a regulatory framework gap assessment in October 2024, reviewing the agency\u2019s regulations and more than 500 regulatory guides, and concluded the existing framework is \u201cgenerally sufficient\u201d to accommodate AI, with only targeted areas identified for further clarification.<\/p>\n Same Number, Different Program: Enter Prometheus<\/p>\n Readers may notice a coincidence worth clarifying: the same day Microsoft announced its $60 million Genesis Mission commitment, the DOE announced a separate $60 million Phase II award<\/a> to the Prometheus project<\/a>, a 32-partner collaboration involving INL, Oak Ridge National Laboratory (ORNL), Argonne National Laboratory, Sandia National Laboratories, academia, and more than 20 industry partners including X-energy, TerraPower, and Oklo. The two efforts are complementary but distinct.<\/p>\n The Prometheus project is considerably larger in scope than a single company\u2019s contribution. Conceived as an integrated AI platform rather than a single tool, Prometheus is meant to link specialized AI agents across the full lifecycle of a nuclear project\u2014design, licensing, manufacturing, construction, and operations\u2014through what ORNL described<\/a> as a \u201cpersistent digital thread\u201d connecting requirements, models, analyses, and records from one stage to the next. The effort has an explicit target: cutting nuclear deployment timelines and operating costs by half. The DOE backed that ambition with a three-year, $60 million Phase II award, subject to appropriations\u2014the first Phase II award made under the Genesis Mission\u2014on top of more than $200 million in industry cost share and $30 million in industry capital the Prometheus team has raised on its own. \u201cAmerica\u2019s nuclear future depends on our ability to move with greater urgency and drive down costs, while maintaining the uncompromising commitment to safety and technical rigor that defines our industry,\u201d INL Director John Wagner said.<\/p>\n It\u2019s unclear how Microsoft\u2019s Azure infrastructure and SPARK program intersect with Prometheus, if at all.<\/p>\n Building Toward What\u2019s Next<\/p>\n Both nuclear projects Microsoft highlighted\u2014the PUR1 autonomous control demonstration and the INL licensing tool\u2014are described by the companies and labs involved as early, deliberately bounded steps: research-reactor scale rather than commercial scale, and document drafting rather than safety analysis. That framing was consistent across Microsoft\u2019s answers and INL\u2019s own project materials, and it sets up a clear next chapter for the Genesis Mission\u2019s nuclear work as SPARK-backed projects mature and as the NRC continues developing its own AI framework in parallel.<\/p>\n Readers who want a closer look at the Genesis Mission\u2019s progress will have the opportunity at POWER\u2019s Experience POWER event<\/a>, Sept. 29\u2013Oct. 1 at the Omni Shoreham in Washington, D.C. Dr. Dario Gil, DOE\u2019s Under Secretary for Science and director of the Genesis Mission, will deliver a keynote on the initiative\u2019s ambitions\u2014from fusion reactors to grid-scale AI\u2014and what it will take to produce dozens of \u201cAlphaFold moments\u201d across science in the next five years. Later that day, a Genesis Mission deep dive session will bring together Microsoft and its mission partners for a closer look at how the initiative is playing out in practice, including the nuclear licensing work at INL discussed in this article. Bryan Lopez will join that panel. Learn more and register to attend at: experience-power.com\/<\/a>.<\/p>\n \u2014Aaron Larson is POWER\u2019s executive editor.<\/p>\n","protected":false},"excerpt":{"rendered":"Last week, Microsoft announced a $60 million, multiyear commitment to the Department of Energy\u2019s (DOE\u2019s) Genesis Mission, the…\n","protected":false},"author":2,"featured_media":121932,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[61604,420,7829,61605,8551,28522,320,7828,61606,14287,7741,1142],"class_list":["post-121931","post","type-post","status-publish","format-standard","has-post-thumbnail","category-microsoft","tag-autonomous-control","tag-azure","tag-azure-ai","tag-doe","tag-genesis-mission","tag-idaho-national-laboratory","tag-microsoft","tag-microsoft-ai","tag-nuclear-licensing","tag-purdue-university","tag-reinforcement-learning","tag-spark"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/121931","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=121931"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/121931\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/121932"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=121931"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=121931"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=121931"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}